4 months ago
Remote, United StatesSenior / Staff+
Base Salary
$170k - $260k/yr
Responsibilities
- Build agent execution systems with autonomous task loops, scheduling, triggers, and control planes.
- Develop retrieval and memory architectures for context management, long-term memory, and structured memory.
- Build multi-model routing and orchestration across providers while balancing quality, latency, cost, and failure modes.
- Create tool-calling and integration frameworks for safe interaction with external services and enterprise environments.
- Develop reliability, security, and operability foundations including evaluation, observability, failure isolation, and recovery paths.
- Build enterprise interfaces and governance surfaces for deploying, managing, monitoring, and controlling AI agents.
- Help determine product direction by understanding users, questioning requirements, and proposing better solutions.
- Use AI throughout design, prototyping, implementation, testing, debugging, and incident response with appropriate guardrails and verification.
Requirements
- Experience building and operating complex backend or distributed systems in production.
- Experience building LLM-powered or AI-native systems beyond demos, with real users and real-world constraints.
- Strong judgment around reliability, security, observability, and failure modes.
- Comfort operating in ambiguous frontier areas and validating ideas through rapid iteration.
- High ownership, autonomy, and ability to take systems end to end.
- TypeScript is required; Python is strongly preferred.
- Strong SQL proficiency.
- Experience with production infrastructure.
- Docker and Kubernetes experience is a plus.
- Familiarity with enterprise security patterns is a plus.
- Domain familiarity with DevOps, SecOps, or infrastructure automation is a plus.
Tech Stack
Categories
About Kindo
Kindo builds an AI-native agent automation platform for enterprise DevOps and SecOps teams, used to execute runbooks, secure infrastructure, and respond to incidents. The product runs on-premises, in hybrid environments, or in the cloud, and includes a domain-tuned DevSecOps LLM compatible with 26+ third-party models. Founded in 2022 and headquartered in Los Angeles, the company is privately held.